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Feature extraction of travel destinations from online Chinese-language customer reviews

机译:从在线中文顾客评论中提取旅游目的地的特征

摘要

Many customers presently browse a large number of online reviews prior to making purchase decisions to access the word-of-mouth comments of other customers about the products and services in which they are interested. Therefore, online customer reviews serve as a feedback mechanism that can help suppliers to improve their products and services, thus gaining competitive advantages. More specifically, the product feature extractions from such reviews are expected to further illuminate the views and attitudes of customers. This study analyses the customer reviews that are posted by Chinese speakers about travel destinations. Our new approach is based on a recently introduced data mining approach that further explores reviews about travel destinations as a particular type of product. Experiments were conducted using datasets comprised of the reviews of three travel destinations in mainland China that had been posted on the internet. The empirical results prove the validity of the proposed method.
机译:当前,许多客户在做出购买决定之前浏览了大量的在线评论,以访问其他客户关于他们感兴趣的产品和服务的口碑评论。因此,在线客户评论是一种反馈机制,可以帮助供应商改善其产品和服务,从而获得竞争优势。更具体地说,从这些评论中提取的产品功能有望进一步阐明客户的观点和态度。这项研究分析了中国讲者发表的有关旅行目的地的顾客评论。我们的新方法基于最近引入的数据挖掘方法,该方法可进一步探索有关旅行目的地作为特定类型产品的评论。实验是使用数据集进行的,该数据集包含在互联网上发布的中国大陆三个旅行目的地的评论。实验结果证明了该方法的有效性。

著录项

  • 作者

    Ye Q; Law R; Li S; Li Y;

  • 作者单位
  • 年度 2011
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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